Eight minutes or less: does the ambulance response time guideline impact trauma patient outcome?

Assessing Efficiency in a Static-Based 9-1-1 Ambulance Service: An Analysis of Operational Performance Metrics

OBJECTIVES

This study sought to evaluate performance indicators to assist a static-based 9-1-1 agency in defining its response efficiency.

METHODS

Initial assessment of three metrics-unit hour utilization (UHU), fractile response intervals, and level 0 frequency (occurrence when no ambulances are available to respond)-suggested the agency's response over its four coverage zones was inefficient, so an operational change was implemented: an ambulance was relocated from one service area to another to improve the overall response productivity. A 2-year retrospective analysis was performed to determine the impact ambulance relocation had on the three targeted measurements.

RESULTS

The operational change resulted in a statistically significant change in unit hour utilization, a non-significant increase in fractile response intervals, and a statistically significant reduction in level 0 frequency from pre- to post-operational change times.

CONCLUSIONS

These findings suggest a way to evaluate the efficiency of static-based ambulance deployment and potentially identify strategies for redeployment.

Comparison of kinetic changes during helicopter medical evacuations: civilian versus military flights

BACKGROUND

Helicopter evacuation is crucial for providing medical care to casualties. Previous civilian studies have demonstrated that air transport can enhance survival rates compared with ground transport. However, there has been limited research on specific accelerations during helicopter flights, particularly in military flights. This study aims to analyse and compare the accelerations endured during civilian and military helicopter evacuations.

METHODS

Accelerations were recorded during evacuation flights from the site of injury to the first medical responders in civilian helicopter EC135 T1, and military Puma SA.330 and Caiman NH90 TTH helicopters. The research investigated global acceleration and compared acceleration distributions along the vertical, lateral and longitudinal axes. A specific comparative study of the take-off phases was also performed.

RESULTS

The analysis showed that vertical loads caused the most extreme accelerations for all types of helicopter but these extreme accelerations were rare and lasted for less than 1 s. Military flights show similar acceleration intensities to civilian flights, but accelerations are higher during short periods of the take-off phase.

CONCLUSIONS

The findings suggest that helicopter evacuations during military operations are as safe as civilian evacuations and highlight the importance of patient positioning in the aircraft. However, further research should investigate the haemodynamic response to accelerations experienced during actual evacuation flights.

Frequency and features of medical emergencies at a teaching dental hospital in Saudi Arabia: a 14-year retrospective observational study

BACKGROUND

This study aimed to determine the nature, frequency, and characteristics of medical emergencies occurring at the King Abdulaziz University Dental Hospital.

MATERIALS AND METHODS

The incident reports of medical emergencies recorded at the King Abdulaziz University Dental Hospital from January 2008 to December 2022 were retrospectively reviewed. The annual/overall incidence of medical emergency events was calculated per 100,000 patients. The following characteristics of the patients/events were evaluated: age, gender, operator, procedure, location, timing of treatment, administration of local anesthesia, past medical history, symptoms, diagnosis, outcome, and disposition. Multivariable logistic regression models were used to investigate the associations of these characteristics with two outcomes: syncope and transfer to the emergency room (ER).

RESULTS

The incidence of emergency events was 17.4 per 100,000 patients. Syncope and hypoglycemia were the most common emergencies. Most incidents recovered, with only 13% requiring transfer to the ER. Undergoing no procedure and American Society of Anesthesiologists (ASA) class 2,3 were associated with syncope. Undergoing a general dental procedure, ASA class 2,3, and a diagnosis other than hypoglycemia and syncope were associated with transfer to the ER.

CONCLUSIONS

The incidence of medical emergencies was low. Dental practitioners need to remain aware of the contributing factors, such as past medical history and anxiety, but medical emergencies can occur in healthy individuals as well. Preparation of the dental office, training of the personnel, and proper recording of the events are essential components of a well-established medical emergency protocol in dental institutions.

Ambulance response times and 30-day mortality: a Copenhagen (Denmark) registry study

BACKGROUND AND IMPORTANCE

Ensuring prompt ambulance responses is complicated and costly. It is a general conception that short response times save lives, but the actual knowledge is limited.

OBJECTIVE

To examine the association between the response times of ambulances with lights and sirens and 30-day mortality.

DESIGN

A registry-based cohort study using data collected from 2014-2018.

SETTINGS AND PARTICIPANTS

This study included 182 895 individuals who, during 2014-2018, were dispatched 266 265 ambulances in the Capital Region of Denmark.

OUTCOME MEASURES AND ANALYSIS

The primary outcome was 30-day mortality. Subgroup analyses were performed on out-of-hospital cardiac arrests, ambulance response priority subtypes, and caller-reported symptoms of chest pain, dyspnoea, unconsciousness, and traffic accidents. The relation between variables and 30-day mortality was examined with logistic regression.

RESULTS

Unadjusted, short response times were associated with higher 30-day mortality rates across unadjusted response time quartiles (0-6.39 min: 9%; 6.40-8.60 min: 7.5%, 8.61-11.80 min: 6.6%, >11.80 min: 5.5%). This inverse relationship was consistent across subgroups, including chest pain, dyspnoea, unconsciousness, and response priority subtypes. For traffic accidents, no significant results were found. In the case of out-of-hospital cardiac arrests, longer response times of up to 10 min correlated with increased 30-day mortality rates (0-6.39 min: 84.1%; 6.40-8.60 min: 86.7%, 8.61-11.8 min: 87.7%, >11.80 min: 85.5%). Multivariable-adjusted logistic regression analysis showed that age, sex, Charlson comorbidity score, and call-related symptoms were associated with 30-day mortality, but response time was not (OR: 1.00 (95% CI [0.99-1.00])).

CONCLUSION

Longer ambulance response times were not associated with increased mortality, except for out-of-hospital cardiac arrests.

Using machine learning to assess the extent of busy ambulances and its impact on ambulance response times: A retrospective observational study

BACKGROUND

Ambulance response times are considered important. Busy ambulances are common, but little is known about their effect on response times.

OBJECTIVE

To assess the extent of busy ambulances in Central Norway and their impact on ambulance response times.

DESIGN

This was a retrospective observational study. We used machine learning on data from nearby incidents to assess the probability of up to five different ambulances being candidates to respond to a medical emergency incident. For each incident, the probability of a busy ambulance was estimated by summing the probabilities of candidate ambulances being busy at the time of the incident. The difference in response time that may be attributable to busy ambulances was estimated by comparing groups of nearby incidents with different estimated busy probabilities.

SETTING

Medical emergency incidents with ambulance response in Central Norway from 2013 to 2022.

MAIN OUTCOME MEASURES

Prevalence of busy ambulances and differences in response times associated with busy ambulances.

RESULTS

The estimated probability of busy ambulances for all 216,787 acute incidents with ambulance response was 26.7% (95% confidence interval (CI) 26.6 to 26.9). Comparing nearby incidents, each 10-percentage point increase in the probability of a busy ambulance was associated with a delay of 0.60 minutes (95% CI 0.58 to 0.62). For incidents in rural and urban areas, the probability of a busy ambulance was 21.6% (95% CI 21.5 to 21.8) and 35.0% (95% CI 34.8 to 35.2), respectively. The delay associated with a 10-percentage point increase in busy probability was 0.81 minutes (95% CI 0.78 to 0.84) and 0.30 minutes (95% CI 0.28 to 0.32), respectively.

CONCLUSION

Ambulances were often busy, which was associated with delayed ambulance response times. In rural areas, the probability of busy ambulances was lower, although the potentially longer delays when ambulances were busy made these areas more vulnerable.

Description and analysis of the emergency obstetric interfacility ambulance transfers (IFTs) to Kawempe National Referral Hospital in Uganda

Introduction

In Uganda, 2% of women die from maternal causes with a mortality rate of 336 maternal deaths per 100,000 live births. According to the World Health Organization Uganda is one of the top three contributors to maternal mortality in sub-Saharan Africa. Uganda has parallel weak ambulance systems, government, and non-government-owned, that transport obstetric emergencies to higher-level facilities. These two operations lack standards of medical care and inter-facility transfer (IFT) protocols to direct care. Limited studies exist which assess the state of Emergency Care Services in Uganda and none has been performed to assess the ambulance referral services utilized to address obstetric emergencies.

Objective

The present study was performed to describe the ambulance transfer processes of obstetric emergencies by analyzing cases arriving at Kawempe National Referral Hospital (KNRH) from outlying health facilities.

Methods

The study was based at KNRH in Kampala, Uganda. It was a descriptive and analytic cross-sectional study. Trained research assistants enrolled participating patients who met the inclusion criteria consecutively on arrival by ambulance at the hospital. Utilizing a questionnaire, quantitative data was collected from the ambulance driver, the sending facility referral form, and the receiving hospital's ambulance log book for each case. The sample size was 215.

Results

The median age was 27 years and the majority of patients were referred because of hypertensive disorders (34.9%), obstructed labor (26.5%) and hemorrhage (20.9%). The median total response time for transfer of obstetric emergencies was 50 min, from ambulance activation until the mother was received at KNRH. Differences were identified between government and non-government-owned ambulances in regards to the method of activation, medical escort staffing, number of vital signs recorded, and ambulance onboard medical care. Ambulances parked at the facility took the shortest transfer time and EMT-supported ambulances had the greatest number of vital signs taken.

Conclusions

Recommendations are to develop an integrated ambulance system for both government and non-government ambulances with standards especially in regards to standardized scripted call-center calls analysis, dispatch activation time, response-to-patient time, and trained ambulance professional staffing and medical care whenever in patient transport mode.

Where to place emergency ambulance vehicles: use of a capacitated maximum covering location model with real call data

This study integrates geographical information systems (GIS) with a mathematical optimization technique to enhance emergency medical services (EMS) coverage in a county in the northeast of Iran. EMS demand locations were determined through one-year EMS call data analysis. We formulated a maximal covering location problem (MCLP) as a mixed-integer linear programming model with a capacity threshold for vehicles using the CPLEX optimizer, an optimization software package from IBM. To ensure applicability to the EMS setting, we incorporated a constraint that maintains an acceptable level of service for all EMS calls. Specifically, we implemented two scenarios: a relocation model for existing ambulances and an allocation model for new ambulances, both using a list of candidate locations. The relocation model increased the proportion of calls within the 5-minute coverage standard from 69% to 75%. With the allocation model, we found that the coverage proportion could rise to 84% of total calls by adding ten vehicles and eight new stations. The incorporation of GIS techniques into optimization modelling holds promise for the efficient management of scarce healthcare resources, particularly in situations where time is of the essence.

Impact of Physical Fitness on Emergency Response: A Case Study of Factors That Influence Individual Responses to Emergencies among University Students

(1) Background: The purpose of this study was to ascertain whether there is a direct correlation between the physical fitness of the general population, specifically students, and the response times to fire-emergency-related building evacuations and to identify which physical fitness factors more significantly influenced emergency movement times. (2) Methods: In this quantitative investigation, 21 students (both men and women of the same age) volunteered to participate. We first evaluated their physical fitness; then, we analyzed their reaction times and speed. (3) Results: The results of this study revealed a relationship between emergency response times and evaluations of muscular strength, muscular endurance, muscle power, cardiorespiratory fitness, and body composition. The physically active group demonstrated a stronger initial response (i.e., a shorter time to reach a safe location) to fictitious emergency scenarios. The reduction in the necessary response time did not, however, appear to be related to the degree of flexibility. (4) Conclusions: This study showed how physical fitness might alter initial emergency response times and lessen the effects of a disaster on the general population.

Identifying Hospital Deserts in Texas Before and During the COVID-19 Outbreak

In this study, we proposed a GIS-based approach to analyzing hospital visitors from January to June 2019 and January to June 2020 with the goal of revealing significant changes in the visitor demographics. The target dates were chosen to observe the effect of the first wave of COVID-19 on the visitor count in hospitals. The results indicated that American Indian and Pacific Islander groups were the only ones that sometimes showed no shift in visitor levels between the studied years. For 19 of the 28 hospitals in Austin, TX, the average distance traveled to those hospitals from home increased in 2020 compared with 2019. A hospital desert index was devised to identify the areas in which the demand for hospitals is greater than the current hospital supply. The hospital desert index considers the travel time, location, bed supply, and population. The cities located along the outskirts of metropolitan regions and rural towns showed more hospital deserts than dense city centers.

Ambulance Response in Eight Minutes or Less: Are Comorbidities a Factor

A recommended emergency medical services ambulance response time to a medical emergency is within eight minutes for at least 90% of calls. This study aimed to evaluate scene times for rural education and outreach to improve the quality of trauma care. This is a single-center study of Trauma Registry data from July 1, 2016 to February 28, 2022. The inclusion criteria were based upon age (≥18 years). A logistic regression was performed to identify predictor variables on the likelihood that an adult trauma patient will experience scene times greater than eight minutes. 19 321 patients were included in the analysis; 7233 (37%) experienced an elapsed scene time within eight minutes. This research identified an opportunity to improve rural trauma team response time, which is only reaching 37% of the patient population within eight minutes. Prehospital cardiac arrest and unique pre-existing comorbidities may play a role in extended response times by EMS.

Use of discrete event simulation and genetic algorithms to estimate the necessary resources to respond in a timely manner in the Medical Emergency System in Bogotá

Introduction

Bogotá has a Medical Emergency System of public and private ambulances that respond to health incidents. However, its sufficiency in quantity, type and location of the resources demanded is not known.

Objective

Based on the data from the Medical Emergency System of Bogotá, Colombia, we first sought to characterize the prehospital re- sponse in cardiac arrest and determine with the model which is the least number of resources necessary to respond within eight minutes, taking into account their location, number, and type.

Methods

A database of incidents reported in administrative records of the district health authority of Bogotá (2014 to 2017) was obtained. Based on this information, a hybrid model based on discrete event simulation and genetic algorithms was designed to establish the amount, type and geographic location of resources according to the frequencies and typology of the events.

Results

From the database, Bogotá presented 938 671 ambulances dispatches in the period. 47.4% high priority, 18.9% medium and 33.74% low. 92% of these corresponded to 15 of 43 medical emergency codes. The response times recorded were longer than expected, especially in out-of-hospital cardiac arrest (median 19 minutes). In the proposed model, the best scenario required at least 281 ambulances, medicalized and basic in a 3:1 ratio, respectively, to respond in adequate time.

Conclusions

Results suggest the need for an increase in the resources that respond to these incidents to bring these response times to the needs of our population.

Response Time and Causes of Delay in Prehospital Emergency Missions in Mashhad, 2015

Background: The response time is considered as one of the most important criteria for the quality of given care to the injured. This research aimed to investigate the frequency and causes of prehospital emergency delays in the 115 emergency center, in city of Mashhad, in 2015.

Methods: In this cross-sectional study, 21,142 missions performed in 2015 were investigated, from among which 640 missions with delays in systematic sampling were recognized. For data analysis purposes, descriptive statistics (frequency, mean and SD) in Excel 2013 software was implemented.

Results: Nearly 60% of the injured were men, 23% women, and the gender of 17% was not recorded in their profiles. The mean age of the injured was 29.8+15.9 years and 30% of the injured were in the age group of 16 to 25. The mean response time was 9:01+2:46. The most prevalent causes related to missions out of the operational zone (29.3%) and the second cause has been related to traffic groups (24.2%).

Conclusion: Establishing new bases and completing the number of ambulances and human recourses, intervention in traffic causing factors, and training the public about emergency cases can be effective in reducing the number of missions and the pace and quality of services provided to the injured.

Does Every Minute Really Count? Road Time as an Indicator for the Economic Value of Emergency Medical Services

OBJECTIVES

This article builds on the literature regarding the association between emergency medical service (EMS) response times and patient outcomes (death and severe injury). Three issues are addressed in this article with respect to the empirical estimation of this relationship: the endogeneity of response time (systematically quicker response for higher degrees of urgency), the nonlinearity of this relationship, and the variation between such estimations for different patient outcomes.

METHODS

Binomial and multinomial logistic regression models are used to estimate the impact of response time on the probabilities of death and severe injury using data from French Fire and Rescue Services. These models are developed with response time as an explanatory variable and then with road time (dispatch to arrival) hypothesized as representing the exogenous variation within response time. Both models are also applied to data subsets based on response time intervals.

RESULTS

The results show that road time yields a higher estimate for the impact of response time on patient outcomes than (total) response time. The impact of road time on patient outcomes is also shown to be nonlinear. These results are of both statistical significance (model coefficients are significant at the 95% confidence level) and economical significance (when taking into account the number of annual interventions performed).

CONCLUSIONS

When using heterogeneous data on EMS interventions where endogeneity is a clear issue, road time is a more reliable indicator to estimate the impact of EMS response time on patient outcomes than (total) response time.

Pandemic hospital site selection: a GIS-based MCDM approach employing Pythagorean fuzzy sets

COVID-19 poses many challenges for hospitals around the world. Each country attempts to solve the problems in its hospitals using different methods. In Turkey, two pandemic hospitals were built in İstanbul, the most crowded province. In addition, some hospitals were designated as pandemic hospitals. This study focuses on the methods used for site selection for a pandemic hospital in Atakum, a district of Samsun City, Turkey. As a solution to the problem, initially, spatial analysis was performed using GIS to produce maps based on seven criteria obtained from the insight of an expert team. Analytic hierarchy process (AHP) augmented by interval-valued Pythagorean fuzzy numbers (PFNs) was then used to determine weights for the criteria. Distance to transportation network was the most important criterion influencing the selection process and the least significant one was the distance to fire stations. Based on the criteria weights, and five rules specified by the expert team, 13 suitable locations for a pandemic hospital were determined using GIS. The technique for order preference by similarity to ideal solution (TOPSIS) method was used to determine the final ranking of 13 alternative locations (A1-A13). A10 was identified as the most appropriate site and A11 as the least appropriate site for a pandemic hospital. Finally, sensitivity analysis was performed to investigate how changes in weight values of the criteria affect the ranking of the alternatives.

Time to Critical Condition in Emergency Services

Providing uninterrupted response service is of paramount importance for emergency medical services, regardless of the operating scenario. Thus, reliable estimates of the time to the critical condition, under which there will be no available servers to respond to the next incoming call, become very useful measures of the system’s performance. In this contribution, we develop a key performance indicator by providing an explicit formula for the average time to the shortage condition. Our analytical expression for this average time is a function of the number of parallel servers and the inter-arrival and service times. We assume exponential distributions of times in our analytical expression, but for evaluating the mean first-passage time to the critical condition under more realistic scenarios, we validate our result through exhaustive simulations with lognormal service time distributions. For this task, we have implemented a simulator in R. Our results indicate that our analytical formula is an acceptable approximation under any situation of practical interest.

Spatial Accessibility Assessment of Prehospital EMS with a Focus on the Elderly Population: A Case Study in Ningbo, China

The spatial accessibility of prehospital EMS is particularly important for the elderly population’s physiological functions. Due to the recent expansion of aging populations all over the globe, elderly people’s spatial accessibility to prehospital EMS presents a serious challenge. An efficient strategy to address this issue involves using geographic information systems (GIS)-based tools to evaluate the spatial accessibility in conjunction with the spatial distribution of aging people, available road networks, and prehospital EMS facilities. This study employed gravity model and empirical Bayesian Kriging (EBK) interpolation analysis to evaluate the elderly’s spatial access to prehospital EMS in Ningbo, China. In our study, we aimed to solve the following specific research questions: In the study area, “what are the characteristics of the prehospital EMS demand of the elderly?” “Do the elderly have equal and convenient spatial access to prehospital EMS?” and “How can we satisfy the prehospital EMS demand of an aging population, improve their spatial access to prehospital EMS, and then ensure their quality of life?” The results showed that 37.44% of patients admitted to prehospital EMS in 2020 were 65 years and older. The rate of utilization of ambulance services by the elderly was 27.39 per 1000 elderly residents. Ambulance use by the elderly was the highest in the winter months and the lowest in the spring months (25.90% vs. 22.38%). As for the disease spectrum, the main disease was found to be trauma and intoxication (23.70%). The mean accessibility score was only 1.43 and nearly 70% of demand points had scored lower than 1. The elderly’s spatial accessibility to prehospital EMS had a central-outward gradient decreasing trend from the central region to the southeast and southwest of the study area. Our proposed methodology and its spatial equilibrium results could be taken as a benchmark of prehospital care capacity and help inform authorities’ efforts to develop efficient, aging-focused spatial accessibility plans.

Correction of the travel time estimation for ambulances of the red cross Tijuana using machine learning

This paper addresses the problem of estimating the response time to a medical emergency, specifically from the Red Cross of Tijuana (RCT), which provides most of the emergency medical services (EMS) in the city of Tijuana, Mexico. For institutions with low funding, such as the RCT, relying on free or open source mapping systems to estimate travel times is necessary but also error prone because these systems are not tuned for ambulance movements within a city. Therefore, this work formulates a supervised machine learning problem where the goal is to predict the difference in travel time between the ground truth travel time provided by a GPS and the approximation offered by two mapping systems, Google Maps (GM) and Open Source Routing Machine (OSRM). To this end, this work develops a new dataset based on the EMS logs of the RCT, considering calls from January 2017 to April 2017. The posed learning problem is solved under different scenarios, including using an off-the-shelf default configuration of a Random Forest classifier, applying a hyper-parameter optimization process and using an Auto Machine Learning (AutoML) system. Considering all of the dataset for GM, test accuracy was 69.6% for the first two learning approaches and 71.6% using AutoML. For OSRM, performance was 64.6%, 65.2% and 66.4% for each of the learning approaches, respectively. Results show that it is possible to predict the level by which a mapping system over or under estimates the true travel time of an ambulance. Finally, the impact of the model is demonstrated by using it to solve the ambulance location problem, with notable differences in ambulance deployments and percentage of double coverage achieved relative to using the standard mapping system. Results show that without correcting the travel time the percentage of double coverage is 83.90%; on the other hand, double coverage reaches 100% when applying travel time correction.

Metaheuristics in the decentralization of SAMU bases using simulation in northeastern Brazil

BACKGROUND AND OBJECTIVE

The growth of the urban population exerts considerable pressure on municipalities' public managers to focus their attention on providing emergency medical care that meets the growing demand for emergency pre-hospital medical care. Currently, there are a significant number of traffic accidents and other serious occurrences, such as heart attacks, drownings, epidemics, fires and disasters (floods, landslides, earthquakes) that demand a prompt and seamless response from pre-hospital medical care. As a result of such scenario, the present article endeavours to apply a dual-coverage mathematical model (DSM-Double Standard Model) to define the optimal location of the Emergency Medical Service (SAMU) decentralized dispatch bases in Natal/RN and conduct a simulation study to evaluate the displacement of ambulances between such bases.

METHODS

The methodological course that was followed by this research constitutes of 12 steps. The location of decentralized bases for sending emergency ambulances was established using the DSM model and the simulation model was performed using the FlexSim© software version 2018 evaluating base coverage in relation to the total number of calls by demand points for different scenarios.

RESULTS

The results obtained throughout the research demonstrated the feasibility of redefining the decentralized bases of SAMU/Natal ambulances as a strategy to reduce response time and guarantee compliance with performance parameters established by international organizations (the World Health Organization, for instance, establishes the time of 8 minutes for emergency medical service calls response). The simulation study showed a significant reduction in response time, by up to 60% in some cases.

CONCLUSION

The proposition of new locations for the decentralized dispatch bases of the SAMU/Natal can provide an overall significant reduction on the ambulance response time, so as to contribute to expedite the initiation of treatment of patients, if necessary, sent to hospitals.

Preserving Geo-Indistinguishability of the Emergency Scene to Predict Ambulance Response Time

Emergency medical services (EMS) provide crucial emergency assistance and ambulatory services. One key measurement of EMS’s quality of service is their ambulances’ response time (ART), which generally refers to the period between EMS notification and the moment an ambulance arrives on the scene. Due to many victims requiring care within adequate time (e.g., cardiac arrest), improving ARTs is vital. This paper proposes to predict ARTs using machine-learning (ML) techniques, which could be used as a decision-support system by EMS to allow a dynamic selection of ambulance dispatch centers. However, one well-known predictor of ART is the location of the emergency (e.g., if it is urban or rural areas), which is sensitive data because it can reveal who received care and for which reason. Thus, we considered the ‘input perturbation’ setting in the privacy-preserving ML literature, which allows EMS to sanitize each location data independently and, hence, ML models are trained only with sanitized data. In this paper, geo-indistinguishability was applied to sanitize each emergency location data, which is a state-of-the-art formal notion based on differential privacy. To validate our proposals, we used retrospective data of an EMS in France, namely Departmental Fire and Rescue Service of Doubs, and publicly available data (e.g., weather and traffic data). As shown in the results, the sanitization of location data and the perturbation of its associated features (e.g., city, distance) had no considerable impact on predicting ARTs. With these findings, EMSs may prefer using and/or sharing sanitized datasets to avoid possible data leakages, membership inference attacks, or data reconstructions, for example.

There Is No Role for Damage Control Orthopedics Within the Golden Hour

INTRODUCTION

Trauma systems within the United States have adapted the "golden hour" principle to guide prehospital planning with the goal to deliver the injured to the trauma facility in under 60 minutes. In an effort to reduce preventable prehospital death, in 2009, Secretary of Defense Robert M. Gates mandated that prehospital transport of injured combat casualties must be less than 60 minutes. The U.S. Military has implemented a 60-minute timeline for the transport of battlefield causalities to medical teams to include Forward Surgical Teams and Forward Resuscitative Surgical Teams. The inclusion of orthopedic surgeons on Forward Surgical Teams has been extrapolated from the concept of damage control orthopedics (DCO). However, it is not clear if orthopedic surgeons have yielded a demonstrable benefit in morbidity or mortality reduction. The purpose of this article is to investigate the function of orthopedic surgeons during the military "golden hour."

MATERIALS AND METHODS

The English literature was reviewed for evidence supporting the use of orthopedic surgeons within the golden hour. Literature was reviewed in light of the 2009 golden hour mandate by Secretary Gates as well as those papers which highlighted the utility of DCO within the golden hour.

RESULTS

Evidence for orthopedic surgery within the "golden hour" or in the current conflicts when the United States enjoys air superiority was not identified.

CONCLUSIONS

Within the military context, DCO, specifically pertaining to fracture fixation, should not be considered an element of golden hour planning and thus orthopedic surgeons are best utilized at more centralized Role 3 facility locations. The focus within the first hour after injury on the battlefield should be maintained on rapid and effective prehospital care combined with timely evacuation, as these are the most critical factors to reducing mortality.

Association of Prehospital Time to In-Hospital Trauma Mortality in a Physician-Staffed Emergency Medicine System

Importance

The association between total prehospital time and mortality in physician-staffed trauma systems remains uncertain.

Objective

To describe the association of total prehospital time and in-hospital mortality in prehospital, physician-staffed trauma systems in France, with the hypothesis that total prehospital time is associated with increased mortality.

Design, Setting, and Participants

This cohort study was conducted from January 2009 to December 2016. Data for this study were derived from 2 distinct regional trauma registries in France (1 urban and 1 rural) that both have a physician-staffed emergency medical service. Consecutive adult trauma patients admitted to either of the regional trauma referral centers during the study period were included. Data analysis took place from March 2018 to September 2018.

Main Outcomes and Measures

The association between death and prehospital time was assessed with a multivariable model adjusted with confounders. Total prehospital time was the primary exposure variable, recorded as the time from the arrival of the physician-led prehospital care team on scene to the arrival at the hospital. The main outcome of interest was all-cause in-hospital mortality.

Results

A total of 10 216 patients were included (mean [SD] age, 41 [18] years; 7937 men [78.3%]) affected by predominantly nonpenetrating injuries (9265 [91.5%]), with a mean (SD) Injury Severity Score of 17 (14) points. Of the patients, 6737 (66.5%) had at least 1 body region with an Abbreviated Injury Scale score of 3 or more. A total of 1259 patients (12.4%) presented in shock (with systolic pressure <90 mm Hg) and 2724 (26.9%) with severe head injury (Abbreviated Injury Scale score ≥3 points). On unadjusted analysis, increasing prehospital times (in 30-minute categories) were associated with a markedly and constant increase in the risk of in-hospital death. The odds of death increased by 9% for each 10-minute increase in prehospital time (odds ratio, 1.09 [95% CI, 1.07-1.11]) and after adjustment by 4% (odds ratio, 1.04 [95% CI, 1.01-1.07]).

Conclusions and Relevance

In this study, an increase in total prehospital time was associated with increasing in-hospital all-cause mortality in trauma patients at a physician-staffed emergency medical system, after adjustment for case complexity. Prehospital time is a management objective in analogy to physiological targets. These findings plead for a further streamlining of prehospital trauma care and the need to define the optimal intervention-to-time ratio.

Identifying patients with time-sensitive injuries: Association of mortality with increasing prehospital time

BACKGROUND

Trauma is a time-sensitive disease. However, recognizing which patients have time-critical injuries in the field is challenging. Many studies failed to identify an association between increasing prehospital time (PHT) and mortality due to evaluation of heterogenous trauma patients, as well as inherent survival bias from missed deaths in patients with long PHT. Our objective was to determine if a subset of existing trauma triage criteria can identify patients in whom mortality is associated with PHT.

METHODS

Trauma patients 16 years or older transported from the scene in the National Trauma Databank 2007 to 2015 were included. Cubic spline analysis used to identify an inflection where mortality increases to identify a marginal population in which PHT is more likely associated with mortality and exclude biased patients with long PHT. Logistic regression determined the association between mortality and PHT, adjusting for demographics, transport mode, vital signs, operative interventions, and complications. Interaction terms between existing trauma triage criteria and PHT were tested, with model stratification across triage criteria with a significant interaction to determine which criteria identify patients that have increased risk of mortality associated with increasing PHT.

RESULTS

Mortality risk increased in patients with total PHT of 30 minutes or less, comprising a study population of 517,863 patients. Median total PHT was 26 minutes (interquartile range, 22-28 minutes) with median Injury Severity Score of 9 (interquartile range, 4-14) and 7.4% mortality. Overall, PHT was not associated with mortality (adjusted odd ratio [AOR], 0.984 per 5-minute increase; 95% confidence interval [CI], 0.960-1.009; p = 0.20). Interaction analysis demonstrated increased mortality associated with increasing PHT for patients with systolic blood pressure less than 90 mm Hg (AOR, 1.039; 95% CI, 1.003-1.078, p = 0.04), Glasgow Coma Scale score of 8 or less (AOR, 1.047; 95% CI, 1.018-1.076; p < 0.01), or nonextremity firearm injury (AOR, 1.049; 95% CI, 1.010-1.089; p < 0.01).

CONCLUSION

Patients with prehospital hypotension, Glasgow Coma Scale score of 8 or less, and nonextremity firearm injury have higher mortality with increasing PHT. These patients may have time-sensitive injuries and benefit from rapid transport to definitive care.

LEVEL OF EVIDENCE

Prognostic/Epidemiologic III; Therapeutic/Care Management IV.

Prehospital times and outcomes of patients who had hypotension at the scene after trauma: A nationwide multicentre retrospective study

BACKGROUND

We aimed to investigate the association between prehospital times and outcomes of patients who had hypotension at the scene after trauma incidents.

METHODS

We retrospectively analysed records from a nationwide database (2004-2017) of adults (aged ≥15 years) who were hypotensive (systolic blood pressure <90 mmHg) at the scene after trauma. The endpoint was in-hospital mortality. We used multivariable logistic regression analysis to adjust for confounding factors and to estimate the odds ratio (OR) of prehospital times for in-hospital mortality. Stratified analyses were performed based on patient age and type and severity of the trauma.

RESULTS

Among 5,499 patients included, 906 (16.5%) died in the hospital. The median Injury Severity Score (ISS) was 17 (interquartile range, 9-29). There was a significant trend towards patients having higher in-hospital mortality and ISS when their prehospital times were shorter (P < 0.001). However, the association between prehospital times and in-hospital mortality was not significant after adjusting for confounding factors, with an adjusted odds ratio of 1.00 (95% confidence interval: 0.98-1.01) per 10 min increments in prehospital time. The association remained insignificant when patients were stratified according to age and type and severity of the trauma.

CONCLUSIONS

Our analysis revealed that prehospital time was not significantly associated with in-hospital mortality among patients who had hypotension at the scene after trauma in the current emergency medical service system in Japan. Further studies are needed to validate our findings.

Identifying quality indicators for prehospital emergency care services in the low to middle income setting: The South African perspective

INTRODUCTION

Historically, performance within the Prehospital Emergency Care (PEC) setting has been assessed primarily based on response times. While easy to measure and valued by the public, overall, response time targets are a poor predictor of quality of care and clinical outcomes. Over the last two decades however, significant progress has been made towards improving the assessment of PEC performance, largely in the form of the development of PEC-specific quality indicators (QIs). Despite this progress, there has been little to no development of similar systems within the low- to middle-income country setting. As a result, the aim of this study was to identify a set of QIs appropriate for use in the South African PEC setting.

METHODS

A three-round modified online Delphi study design was conducted to identify, refine and review a list of QIs for potential use in the South African PEC setting. Operational definitions, data components and criteria for use were developed for 210 QIs for inclusion into the study.

RESULTS

In total, 104 QIs reached consensus agreement including, 90 clinical QIs, across 15 subcategories, and 14 non-clinical QIs across two subcategories. Amongst the clinical category, airway management (n = 13 QIs; 14%); out-of-hospital cardiac arrest (n = 13 QIs; 14%); and acute coronary syndromes (n = 11 QIs; 12%) made up the majority. Within the non-clinical category, adverse events made up the significant majority with nine QIs (64%).

CONCLUSION

Within the South Africa setting, there are a multitude of QIs that are relevant and appropriate for use in PEC. This was evident in the number, variety and type of QIs reaching consensus agreement in our study. Furthermore, both the methodology employed, and findings of this study may be used to inform the development of PEC specific QIs within other LMIC settings.

Using optimization to provide decision support for strategic emergency medical service planning - Three case studies

To achieve high performing emergency medical services (EMS), planning is of vital importance. EMS planners face several challenges when managing ambulance stations and the fleet of ambulances. In this paper, three strategic cases for EMS planners are presented together with potential solutions. In the first case, the effects of closing down a local emergency room (ER) are analyzed together with how adding an ambulance station and an ambulance to the area affected by the closing of the ER can be used to mitigate the negative consequences from the closing. The second case investigates a change in the organization of EMS. Currently, many non-urgent transport assignments are performed by ambulances which make them unavailable for more urgent calls. The potential for a more effective utilization of the ambulances is explored through transferring these assignments to designated transport vehicles. The third case is more technical and challenges the common practice regarding how time dependent demand is handled. Looking at the busiest hour or the average daily demand, is compared with taking time varying demand into account. The cases and solutions are studied using a recently developed strategic ambulance station location and ambulance allocation model for the Maximum Expected Performance Location Problem with Heterogeneous Regions (MEPLP-HR). The model has been extended to also include multiple time periods. This article demonstrates an innovative use of the model and how it can be applied to find and evaluate solutions to real cases within the field of strategic planning of EMS. The model is found to be a useful decision support tool when analyzing the cases and the expected performance of potential solutions.

Impact of time spent in the trauma bay on mortality outcomes among level 1 trauma patients

Introduction

The majority of trauma-related deaths occur within the first 24 h of injury, and time elapsed until intervention for an injury is one of the greatest causes of preventable death in mature trauma centers. This study seeks to determine if there is a correlation between time spent in the trauma bay and mortality outcomes.

Methods

A retrospective analysis of Level 1 trauma patients from 1 January 2010 to 1 January 2016 in a single center.

Results

Charts from 1678 Level 1 trauma patients with 1290 (76.9%) blunt and 388 (23.1%) penetrating injuries were analyzed. Of these, 345 patients died and 237 (68.7%) died within the first 24 h. Multivariate analysis yields an inverse correlation between increased times spent in the trauma bay and mortality, with controls for injury severity, age, and race/ethnicity and with deaths in the trauma bay excluded ( p < 0.001). Each additional minute spent in the trauma bay increases odds of surviving by 1%. However, increase in ISS and decrease in TRISS were directly correlated with reduced time in the trauma bay for both blunt and penetrating traumas. Results did not differ based on mechanism of injury or destination after the trauma bay.

Conclusion

Reduced time spent in trauma bay was not correlated with improved mortality outcomes in Level 1 trauma patients. Findings do not necessarily suggest that increased trauma bay time would reduce mortality, but rather current evaluation procedures may prioritize trauma patients appropriately. Instinctive adjustment by emergency care providers to move more severely injured patients out of the trauma bay quicker and other additional variables could account for the measured phenomena. This is the first study to examine trauma bay times and mortality outcomes.

The affordable care act and ambulance response times

This study contributes to the literature on the capacity challenges faced by health care providers after insurance expansions by examining the Affordable Care Act (ACA) and ambulance response times. Exploiting temporal and geographic variation in the implementation of the ACA as well as pre-treatment differences in uninsured rates, we estimate that the expansions of private and Medicaid coverage under the ACA combined to slow ambulance response times by an average of 24%. We conclude that, through extending coverage to individuals who, in its absence, would not have availed themselves of emergency medical services, the ACA added strain to emergency response systems.

Pre-hospital care of road traffic accident victims in the Niger Delta: a private initiative and experience

This is a review of pre-hospital care of road traffic accident (RTA) victims in the Niger Delta covering the highway linking Benin to Warri in Delta State, Nigeria, from January to December (2017). The non-availability of these services in the South South Nigeria prompted this initiative. Ambulance services with technicians and doctors attended the patients when accidents occurred. This was done in collaboration with the Nigeria Red Cross, Police, Army, and Road safety patrol teams. The information from the patrol team through dedicated lines initiated the emergency response. Response time was an average of 10-30 minutes. A major benefit of this initiative is early commencement of resuscitation and prevention of secondary injuries. A total of 70 RTA victims were salvaged from the accident scene by the Red Cross Society in 2017. A total of 29 RTA patients were salvaged through this initiative in 2017, in Delta State, Nigeria. The main challenges of this effort were delayed communication, insufficient ambulance manpower, and limited funding. Government involvement in public enlightenment, training paramedics, and provision of ambulance services to reduce deaths on our highways is needed.

Longer Prehospital Time was not Associated with Mortality in Major Trauma: A Retrospective Cohort Study

Objective: The objective of this study was to determine the association between prehospital time and outcomes in adult major trauma patients, transported by ambulance paramedics. Methods: A retrospective cohort study of major trauma patients (Injury Severity Score >15) attended by St John Ambulance paramedics in Perth, Western Australia, who were transported to hospital between January 1, 2013 and December 31, 2016. Inverse probability of treatment weighting (IPTW) using the propensity score was performed to limit selection bias and confounding. The primary outcome was 30-day mortality and the secondary outcome was the length of hospital stay (LOS) for 30-day survivors. Multivariate logistic and log-linear regression analyses with IPTW were used to determine if prehospital time of more than the one hour (from receipt of the emergency call to arrival at hospital) or any individual prehospital time interval (response, on-scene, transport, or total time) was associated with 30-day mortality or LOS. Results: A total of 1,625 major trauma patients were included and 1,553 included in the IPTW sample. No significant association between prehospital time of one hour and 30-day mortality was found (adjusted odds ratio 1.10, 95% confidence interval (CI) 0.71-1.69). No association between any individual prehospital time interval and 30-day mortality was identified. In the 30-day survivors, one-minute increase of on-scene time was associated with 1.16 times (95% CI 1.03-1.31) longer LOS. Conclusion: Longer prehospital times were not associated with an increased likelihood of 30-day mortality in major trauma patients transported to hospital by ambulance paramedics. We found no evidence to support the hypothesis that prehospital time longer than one hour resulted in an increased risk of 30-day mortality. However, longer on-scene time was associated with longer hospital LOS (for 30-day survivors). Our recommendation is that prehospital care is delivered in a timely fashion and delivery of the patient to hospital is reasonably prompt.

A Vulnerability Assessment of Urban Emergency in Schools of Shanghai

Schools and students are particularly vulnerable to natural hazards, especially pluvial flooding in cities. This paper presents a scenario-based study that assesses the school vulnerability of emergency services (i.e., Emergency Medical Service and Fire & Rescue Service) to urban pluvial flooding in the city center of Shanghai, China through the combination of flood hazard analysis and GIS-based accessibility mapping. Emergency coverages and response times in various traffic conditions are quantified to generate school vulnerability under normal no-flood and 100-y pluvial flood scenarios. The findings indicate that severe pluvial flooding could lead to proportionate and linear impacts on emergency response provision to schools in the city. Only 11% of all the schools is predicted to be completely unreachable (very high vulnerability) during flood emergency but the majority of the schools would experience significant delay in the travel times of emergency responses. In this case, appropriate adaptations need to be particularly targeted for specific hot-spot areas (e.g., new urbanized zones) and crunch times (e.g., rush hours).

Quality Indicators for Evaluating Prehospital Emergency Care: A Scoping Review

Introduction Historically, the quality and performance of prehospital emergency care (PEC) has been assessed largely based on surrogate, non-clinical endpoints such as response time intervals or other crude measures of care (eg, stakeholder satisfaction). However, advances in Emergency Medical Services (EMS) systems and services world-wide have seen their scope and reach continue to expand. This has dictated that novel measures of performance be implemented to compliment this growth. Significant progress has been made in this area, largely in the form of the development of evidence-informed quality indicators (QIs) of PEC. Problem Quality indicators represent an increasingly popular component of health care quality and performance measurement. However, little is known about the development of QIs in the PEC environment. The purpose of this study was to assess the development and characteristics of PEC-specific QIs in the literature.

METHODS

A scoping review was conducted through a search of PubMed (National Center for Biotechnology Information, National Institutes of Health; Bethesda, Maryland USA); EMBase (Elsevier; Amsterdam, Netherlands); CINAHL (EBSCO Information Services; Ipswich, Massachusetts USA); Web of Science (Thomson Reuters; New York, New York USA); and the Cochrane Library (The Cochrane Collaboration; Oxford, United Kingdom). To increase the sensitivity of the literature, a search of the grey literature and review of select websites was additionally conducted. Articles were selected that proposed at least one PEC QI and whose aim was to discuss, analyze, or promote quality measurement in the PEC environment.

RESULTS

The majority of research (n=25 articles) was published within the last decade (68.0%) and largely originated within the USA (68.0%). Delphi and observational methodologies were the most commonly employed for QI development (28.0%). A total of 331 QIs were identified via the article review, with an additional 15 QIs identified via the website review. Of all, 42.8% were categorized as primarily Clinical, with Out-of-Hospital Cardiac Arrest contributing the highest number within this domain (30.4%). Of the QIs categorized as Non-Clinical (57.2%), Time-Based Intervals contributed the greatest number (28.8%). Population on Whom the Data Collection was Constructed made up the most commonly reported QI component (79.8%), followed by a Descriptive Statement (63.6%). Least reported were Timing of Data Collection (12.1%) and Timing of Reporting (12.1%). Pilot testing of the QIs was reported on 34.7% of QIs identified in the review.

CONCLUSION

Overall, there is considerable interest in the understanding and development of PEC quality measurement. However, closer attention to the details and reporting of QIs is required for research of this type to be more easily extrapolated and generalized. Howard I , Cameron P , Wallis L , Castren M , Lindstrom V . Quality indicators for evaluating prehospital emergency care: a scoping review. Prehosp Disaster Med. 2018;33(1):43-52.

Simulation-based decision support framework for dynamic ambulance redeployment in Singapore

OBJECTIVE

Dynamic ambulance redeployment policies tend to introduce much more flexibilities in improving ambulance resource allocation by capitalizing on the definite geospatial-temporal variations in ambulance demand patterns over the time-of-the-day and day-of-the-week effects. A novel modelling framework based on the Approximate Dynamic Programming (ADP) approach leveraging on a Discrete Events Simulation (DES) model for dynamic ambulance redeployment in Singapore is proposed in this paper.

METHODS

The study was based on the Singapore's national Emergency Medical Services (EMS) system. Based on a dataset comprising 216,973 valid incidents over a continuous two-years study period from 1 January 2011-31 December 2012, a DES model for the EMS system was developed. An ADP model based on linear value function approximations was then evaluated using the DES model via the temporal difference (TD) learning family of algorithms. The objective of the ADP model is to derive approximate optimal dynamic redeployment policies based on the primary outcome of ambulance coverage.

RESULTS

Considering an 8min response time threshold, an estimated 5% reduction in the proportion of calls that cannot be reached within the threshold (equivalent to approximately 8000 dispatches) was observed from the computational experiments. The study also revealed that the redeployment policies which are restricted within the same operational division could potentially result in a more promising response time performance. Furthermore, the best policy involved the combination of redeploying ambulances whenever they are released from service and that of relocating ambulances that are idle in bases.

CONCLUSION

This study demonstrated the successful application of an approximate modelling framework based on ADP that leverages upon a detailed DES model of the Singapore's EMS system to generate approximate optimal dynamic redeployment plans. Various policies and scenarios relevant to the Singapore EMS system were evaluated.

Experimental Simulation-Based Performance Evaluation of an SMS-Based Emergency Geolocation Notification System

In an emergency, a prompt response can save the lives of victims. This statement generates an imperative issue in emergency medical services (EMS). Designing a system that brings simplicity in locating emergency scenes is a step towards improving response time. This paper therefore implemented and evaluated the performance of an SMS-based emergency geolocation notification system with emphasis on its SMS delivery time and the system's geolocation and dispatch time. Using the RAS metrics recommended by IEEE for evaluation, the designed system was found to be efficient and effective as its reliability stood within 62.7% to 70.0% while its availability stood at 99% with a downtime of 3.65 days/year.

Not all prehospital time is equal: Influence of scene time on mortality

BACKGROUND

Trauma is time sensitive, and minimizing prehospital (PH) time is appealing. However, most studies have not linked increasing PH time with worse outcomes because raw PH times are highly variable. It is unclear whether specific PH time patterns affect outcomes. Our objective was to evaluate the association of PH time interval distribution with mortality.

METHODS

Patients transported by emergency medical services in the Pennsylvania trauma registry from 2000 to 2013 with a total PH time (TPT) of 20 minutes or longer were included. TPT was divided into three PH time intervals: response, scene, and transport time. The number of minutes in each PH time interval was divided by TPT to determine the relative proportion each interval contributed to TPT. A prolonged interval was defined as any one PH interval contributing equal to or greater than 50% of TPT. Patients were classified by prolonged PH interval or no prolonged PH interval (all intervals < 50% of TPT). Patients were matched for TPT, and conditional logistic regression determined the association of mortality with PH time pattern, controlling for confounders. PH interventions were explored as potential mediators, and PH triage criteria used identify patients with time-sensitive injuries.

RESULTS

There were 164,471 patients included. Patients with prolonged scene time had increased odds of mortality (odds ratio, 1.21; 95% confidence interval, 1.02-1.44; p = 0.03). Prolonged response, transport, and no prolonged interval were not associated with mortality. When adjusting for mediators including extrication and PH intubation, prolonged scene time was no longer associated with mortality (odds ratio, 1.06; 95% confidence interval, 0.90-1.25; p = 0.50). Together, these factors mediated 61% of the effect between prolonged scene time and mortality. Mortality remained associated with prolonged scene time in patients with hypotension, penetrating injury, and flail chest.

CONCLUSION

Prolonged scene time is associated with increased mortality. PH interventions partially mediate this association. Further study should evaluate whether these interventions drive increased mortality because they prolong scene time or by another mechanism, as reducing scene time may be a target for intervention.

LEVEL OF EVIDENCE

Prognostic/epidemiologic study, level III.

Ubiquitous Emergency Medical Service System Based on Wireless Biosensors, Traffic Information, and Wireless Communication Technologies: Development and Evaluation

This study presents a new ubiquitous emergency medical service system (UEMS) that consists of a ubiquitous tele-diagnosis interface and a traffic guiding subsystem. The UEMS addresses unresolved issues of emergency medical services by managing the sensor wires for eliminating inconvenience for both patients and paramedics in an ambulance, providing ubiquitous accessibility of patients' biosignals in remote areas where the ambulance cannot arrive directly, and offering availability of real-time traffic information which can make the ambulance reach the destination within the shortest time. In the proposed system, patient's biosignals and real-time video, acquired by wireless biosensors and a webcam, can be simultaneously transmitted to an emergency room for pre-hospital treatment via WiMax/3.5 G networks. Performances of WiMax and 3.5 G, in terms of initialization time, data rate, and average end-to-end delay are evaluated and compared. A driver can choose the route of the shortest time among the suggested routes by Google Maps after inspecting the current traffic conditions based on real-time CCTV camera streams and traffic information. The destination address can be inputted vocally for easiness and safety in driving. A series of field test results validates the feasibility of the proposed system for application in real-life scenarios.

Rural risk: Geographic disparities in trauma mortality

BACKGROUND

Barriers to trauma care for rural populations are well documented, but little is known about the magnitude of urban-rural disparities in injury mortality. This study sought to quantify differences in injury mortality comparing rural and nonrural residents with traumatic injuries.

METHODS

Using data from the 2009-2010 Nationwide Emergency Department Sample, multiple logistic regression analyses were conducted to estimate odds of death after traumatic injury for rural residents compared with nonrural residents, while controlling for age, sex, injury type and severity, comorbidities, trauma designation, and Census region.

RESULTS

Rural residents were 14% more likely to die after traumatic injury compared with nonrural residents (P < .001). Increased odds of death for rural residents were observed at level I (odds ratio = 1.20, P < .001), level II (odds ratio = 1.34, P < .001), and level IV/nontrauma centers (odds ratio = 1.23, P < .001). The disparity was greatest for injuries occurring in the South and Midwest (odds ratio = 1.54, P < .001 and odds ratio = 2.06, P < .001, respectively) and for cases with an injury severity score <9 or unknown severity (odds ratio = 2.09, P < .001 and odds ratio = 1.31, P < .001, respectively).

CONCLUSION

Rural residents are significantly more likely than nonrural residents to die after traumatic injury. This disparity varies by trauma center designation, injury severity, and US Census region. Distance and time to treatment likely play a role in rural injury outcomes, along with regional differences in prehospital care and trauma system organization.

Optimizing the location of ambulances in Tijuana, Mexico

In this work we report on modeling the demand for Emergency Medical Services (EMS) in Tijuana, Baja California, Mexico, followed by the optimization of the location of the ambulances for the Red Cross of Tijuana (RCT), which is by far the largest provider of EMS services in the region. We used data from more than 10,000 emergency calls surveyed during the year 2013 to model and classify the demand for EMS in different scenarios that provide different perspectives on the demand throughout the city, considering such factors as the time of day, work and off-days. A modification of the Double Standard Model (DSM) is proposed and solved to determine a common robust solution to the ambulance location problem that simultaneously satisfies all specified constraints in all demand scenarios selecting from a set of almost 1000 possible base locations. The resulting optimization problems are solved using integer linear programming and the solutions are compared with the locations currently used by the Red Cross. Results show that demand coverage and response times can be substantially improved by relocating the current bases without the need for additional resources.

Population-level Spatial Access to Prehospital Care by the National Ambulance Service in Ghana

BACKGROUND

Conditions requiring emergency treatment disproportionately affect low- and middle-income countries (LMICs), where there is often insufficient prehospital care capacity. To inform targeted prehospital care development in Ghana, we aimed to describe spatial access to formal prehospital care services and identify ambulance stations for capacity expansion.

METHODS

Cost distance methods were used to evaluate areal and population-level access to prehospital care within 30 and 60 minutes of each of the 128 ambulance stations in Ghana. With network analysis methods, a two-step floating catchment area model was created to identify district-level variability in access. Districts without NAS stations within their catchment areas were identified as candidates for an additional NAS station. Additionally, five candidate stations for capacity expansion (e.g., addition of an ambulance) were then identified through iterative simulations that were designed to identify the stations that had the greatest influence on the access scores of the ten lowest access districts.

RESULTS

Following NAS inception, the proportion of Ghana's landmass serviceable within 60 minutes of a station increased from 8.7 to 59.4% from 2004 to 2014, respectively. Over the same time period, the proportion of the population with access to the NAS within 60-minutes increased from 48% to 79%. The two-step floating catchment area model identified considerable variation in district-level access scores, which ranged from 0.05 to 2.43 ambulances per 100,000 persons (median 0.45; interquartile range 0.23-0.63). Seven candidate districts for NAS station addition and five candidate NAS stations for capacity expansion were identified. The addition of one ambulance to each of the five candidate stations improved access scores in the ten lowest access districts by a total 0.22 ambulances per 100,000 persons.

CONCLUSIONS

The NAS in Ghana has expanded its population-level spatial access to the majority of the population; however, access inequality exists in both rural and urban areas that can be improved by increasing station capacity or adding additional stations. Geospatial methods to identify access inequities and inform service expansion might serve as a model for other LMICs attempting to understand and improve formal prehospital care services.

Home healthcare nurses’ experiences of being on stand by as a first responder in a ‘While Waiting For the Ambulance’ assignment

The aim of the study is to describe experiences of the ‘While Waiting for the Ambulance’ (WWFA) assignment, as described by home healthcare nurses (HHCNs). Since the early 1990s, municipal resources in Sweden, preferably firefighters, have been dispatched on WWFA. In order to further assist the local residents on an island in the southwest of Sweden, HHCNs have recently begun accompanying firefighters on WWFA. A reflective lifeworld approach was used for data analysis including in-depth interviews with eight HHCNs. When WWFA was established, the HHCNs experienced lack of clarity in where their responsibilities start and end. A split role is described, and there is a paradox in that the responders are meant to collaborate toward saving lives, when the assignment itself has a lack of collaborative structure. Ethical dilemmas and inner emotional worries led to the nurses expressing a need for support before, during and after WWFA.

Ambulance Transfer in Case of Postpartum Hemorrhage after Birth in Primary Midwifery Care in The Netherlands: A Prospective Cohort Study

BACKGROUND

The objective of this prospective cohort study was to assess whether the 45-minute prehospital limit for ambulance transfer is met in case of postpartum hemorrhage (PPH) after midwifery-supervised home birth in The Netherlands and evaluate the process of ambulance transfer, maternal condition during transfer, and outcomes in relation to whether this limit was met.

METHODS

Using ambulance report forms and medical charts, ambulance intervals, urgency coding, clinical condition (using the lowest Revised Trauma Score, [RTS]), and maternal outcomes were collected. From April 2008 to April 2010, midwives reported 72 cases of PPH. Associations between duration of the ambulance transfer, maternal condition during ambulance transfer and outcomes were analyzed. The main outcome measures were duration of ambulance transfer, RTS, blood loss, surgical procedures, and blood transfusions.

RESULTS

Seventy-two cases were reported, 18 (25%) were excluded: 54 cases were analyzed. In 63 percent, the 45-minute prehospital limit was met, 75.9 percent received a RTS of 12, indicating optimal Glasgow Coma Scale, systolic blood pressure, and respiratory frequency. In 24.1 percent a decrease in systolic blood pressure was found (RTS 10 or 11). We found no difference in outcomes between women with different RTS or in whom the 45-minute prehospital limit was or was not met.

CONCLUSIONS

We found no relation between the duration of ambulance transfer and maternal condition or outcomes. All women fully recovered. The low-risk profile of women in primary care, well-organized midwifery, and ambulance care in The Netherlands are likely to contribute to these findings.

Does the Implementation of an Advanced Life Support Quick Response Vehicle (QRV) in an Integrated Fire/EMS System Improve Patient Contact Response Time?

Background

The current Fire/Emergency Medical Services (EMS) model throughout the United States involves emergency vehicles which respond from a primary location (ie, firehouse or municipal facility) to emergency calls. Quick response vehicles (QRVs) have been used in various Fire/EMS systems; however, their effectiveness has never been studied.

Objectives

The goal of this study was to determine if patient response times would decrease by placing an Advanced Life Support (ALS) QRV in an integrated Fire/EMS system.

Methods

Response times from an integrated Fire/EMS system with an annual EMS call volume of 3,261 were evaluated over the three years prior to the implementation of this study. For a 2-month period, an ALS QRV staffed by a firefighter/paramedic responded to emergency calls during peak call volume hours of 8:00 am to 5:00 pm. The staging of this vehicle was based on historical call volume percentages using respective geocodes as well as system requirements during multiple emergency dispatches.

Results

Prior to the study, the citywide average response time for the twelve months preceding was 5.44 minutes. During the study, the citywide average response time decreased to 4.09 minutes, resulting in a 27.62% reduction in patient response time.

Conclusion

The implementation of an ALS QRV in an integrated Fire/EMS system reduces patient response time. Having a QRV that is not staged continuously in a traditional fire station or municipal location reduces the time needed to reach patients. Also, using predictive models of historic call volume can aid Fire and EMS administrators in reduction of call response times.

AndersonDW, DhindsaHS, WanW, SalotD. Does the implementation of an Advanced Life Support quick response vehicle (QRV) in an integrated Fire/EMS system improve patient contact response time?Prehosp Disaster Med. 2015;30(4):1 – 3.

Knowledge and Beliefs of EMS Providers toward Lights and Siren Transportation

Introduction

The use of warning lights and siren (WLS) increases the risk of ambulance collisions. Multiple studies have failed to demonstrate a clinical benefit to the patients. We sought to investigate the degree to which providers understand the data and incorporate it into their practice.

Methods

The authors distributed an anonymous survey to prehospital providers under their medical direction at staff and quality assurance meetings. The surveys asked the providers’ degree of agreement with four statements: transport with lights and siren shortens transport times; transport with lights and siren improves patient outcome; transport with lights and siren increases the risk of collision during transport; and transport with lights and siren reduces the utilization of “mutual aid” service. We compared responses between providers who had been in prior ambulance collisions and those who had not.

Results

Few responses reached statistical significance, but respondents tended towards agreement that WLS use shortens transport times, that it does not improve outcomes, and that it increases the risk of collision. Despite the overall agreement with the published literature, respondents report >80% of transports are conducted using WLS.

Conclusion

The data demonstrate the surveyed providers are aware of the risk posed by WLS to themselves, their patients, and the public. Nevertheless, their practice in the absence of rigid protocols suggests they disregard this knowledge. Despite a large number of prior ambulance collisions among the surveyed group, a high number of transports are conducted using WLS.

Emergency room (ER) referrals and health insurance in the United States

This article aims to determine how various health insurance policies affect the rate of emergency room (ER) referrals in the United States. The secondary data, gathered in National Health Measurement Study (NHMS) in 2008 and 2010, was used. The authors identify the relationships between health insurance and ER referrals by using zero-inflated binomial and zero-inflated Poisson regression. About 17% (2008) and 20% (2010) of the respondents had one or more ER referrals in the 2 years; those who were under coverage of governmental health insurance are more likely to refer ER than uninsured group. The differences in ER referrals that ended with hospital admission across different insurance policies are not significant. Health insurance is a remarkable factor in ER referrals; the coverage of health insurance plans can affect consuming the services provided in ER. Governmental insurance plans can increase ER referrals.

Revisiting the "Golden Hour": An Evaluation of Out-of-Hospital Time in Shock and Traumatic Brain Injury

STUDY OBJECTIVE

We evaluate patients with shock and traumatic brain injury who were previously enrolled in an out-of-hospital clinical trial to test the association between out-of-hospital time and outcome.

METHODS

This was a secondary analysis of patients with shock and traumatic brain injury who were aged 15 years or older and enrolled in a Resuscitation Outcomes Consortium out-of-hospital clinical trial by 81 emergency medical services agencies transporting to 46 Level I and II trauma centers in 11 sites (May 2006 through May 2009). Inclusion criteria were systolic blood pressure less than or equal to 70 mm Hg or systolic blood pressure 71 to 90 mm Hg with pulse rate greater than or equal to 108 beats/min (shock cohort) and Glasgow Coma Scale score less than or equal to 8 (traumatic brain injury cohort); patients meeting both criteria were placed in the shock cohort. Primary outcomes were 28-day mortality (shock cohort) and 6-month Glasgow Outcome Scale-Extended score less than or equal to 4 (traumatic brain injury cohort).

RESULTS

There were 778 patients in the shock cohort (26% 28-day mortality) and 1,239 patients in the traumatic brain injury cohort (53% 6-month Glasgow Outcome Scale-Extended score ≤4). Out-of-hospital time greater than 60 minutes was not associated with worse outcomes after accounting for important confounders in the shock cohort (adjusted odds ratio [aOR] 1.42; 95% confidence interval [CI] 0.77 to 2.62) or traumatic brain injury cohort (aOR 0.77; 95% CI 0.51 to 1.15). However, shock patients requiring early critical hospital resources and arriving after 60 minutes had higher 28-day mortality (aOR 2.37; 95% CI 1.05 to 5.37); this finding was not observed among a similar traumatic brain injury subgroup.

CONCLUSION

Among out-of-hospital trauma patients meeting physiologic criteria for shock and traumatic brain injury, there was no association between time and outcome. However, the subgroup of shock patients requiring early critical resources and arriving after 60 minutes had higher mortality.